Dataset Information

Allele frequency changes due to hitch-hiking in genomic selection programs.

ABSTRACT:

Background

Genomic selection makes it possible to reduce pedigree-based inbreeding over best linear unbiased prediction (BLUP) by increasing emphasis on own rather than family information. However, pedigree inbreeding might not accurately reflect loss of genetic variation and the true level of inbreeding due to changes in allele frequencies and hitch-hiking. This study aimed at understanding the impact of using long-term genomic selection on changes in allele frequencies, genetic variation and level of inbreeding.

Methods

Selection was performed in simulated scenarios with a population of 400 animals for 25 consecutive generations. Six genetic models were considered with different heritabilities and numbers of QTL (quantitative trait loci) affecting the trait. Four selection criteria were used, including selection on own phenotype and on estimated breeding values (EBV) derived using phenotype-BLUP, genomic BLUP and Bayesian Lasso. Changes in allele frequencies at QTL, markers and linked neutral loci were investigated for the different selection criteria and different scenarios, along with the loss of favourable alleles and the rate of inbreeding measured by pedigree and runs of homozygosity.

Results

For each selection criterion, hitch-hiking in the vicinity of the QTL appeared more extensive when accuracy of selection was higher and the number of QTL was lower. When inbreeding was measured by pedigree information, selection on genomic BLUP EBV resulted in lower levels of inbreeding than selection on phenotype BLUP EBV, but this did not always apply when inbreeding was measured by runs of homozygosity. Compared to genomic BLUP, selection on EBV from Bayesian Lasso led to less genetic drift, reduced loss of favourable alleles and more effectively controlled the rate of both pedigree and genomic inbreeding in all simulated scenarios. In addition, selection on EBV from Bayesian Lasso showed a higher selection differential for mendelian sampling terms than selection on genomic BLUP EBV.

Conclusions

Neutral variation can be shaped to a great extent by the hitch-hiking effects associated with selection, rather than just by genetic drift. When implementing long-term genomic selection, strategies for genomic control of inbreeding are essential, due to a considerable hitch-hiking effect, regardless of the method that is used for prediction of EBV.

SUBMITTER: Liu H

PROVIDER: S-EPMC3942192 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Publications

Allele frequency changes due to hitch-hiking in genomic selection programs.

Liu Huiming H Sørensen Anders C AC Meuwissen Theo H E TH Berg Peer P

Genetics, selection, evolution : GSE 20140204

<h4>Background</h4>Genomic selection makes it possible to reduce pedigree-based inbreeding over best linear unbiased prediction (BLUP) by increasing emphasis on own rather than family information. However, pedigree inbreeding might not accurately reflect loss of genetic variation and the true level of inbreeding due to changes in allele frequencies and hitch-hiking. This study aimed at understanding the impact of using long-term genomic selection on changes in allele frequencies, genetic variati ...[more]

PMID: 24495634

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Project description:Survivor populations of red clover (Trifolium pratense L.) from plots in a field experiment in southern Norway were genetically characterized using genotyping by sequencing, and compared with the original population and each other. Genetic differentiation between populations was characterized on the basis of allele frequencies of single nucleotide polymorphisms (SNPs), using principal component analysis. SNPs that had been under selection, i.e., SNPs with significantly different allele frequencies in survivor populations relative to the original population, or between survivor populations that had received different treatments, were identified by analysis of F ST values, using BayeScan and a simple and stringent F ST-based test utilizing replicate populations from the field experiment. In addition, we tested the possibility of pooling DNA samples prior to sequencing, and pooling leaf samples prior to DNA extraction and sequencing, followed by allele frequency estimation on the basis of number of variant reads. Overall, survivor populations were more different from each other than from the original population, indicating random changes in allele frequency, selection in response to local variation in conditions between plots in the field experiment, or sampling error. However, some differentiation was observed between plots sown as pure stands or species mixtures, plots sown at different densities, and plots subjected to different harvesting regimes. Allele frequencies could be accurately estimated from pooled DNA, and SNPs under selection could be identified when leaf samples were pooled prior to DNA extraction. However, substantial sampling error required replicate populations and/or a high number of sampled individuals. We identified a number of chromosomal loci that had been under selection in pure stand plots relative to the original sown population, and loci that had been under differential selection in pure stands of red clover vs. red clover grown in species mixtures. These are all candidate loci for establishment success or persistence in red clover.

Project description:BACKGROUND: Allele frequency is one of the most important population indices and has been broadly applied to genetic/genomic studies. Estimation of allele frequency using genotypes is convenient but may lose data information and be sensitive to genotyping errors. RESULTS: This study utilizes a unified intensity-measuring approach to estimating individual-level allele frequencies for 1,104 and 1,270 samples genotyped with the single-nucleotide-polymorphism arrays of the Affymetrix Human Mapping 100K and 500K Sets, respectively. Allele frequencies of all samples are estimated and adjusted by coefficients of preferential amplification/hybridization (CPA), and large ethnicity-specific and cross-ethnicity databases of CPA and allele frequency are established. The results show that using the CPA significantly improves the accuracy of allele frequency estimates; moreover, this paramount factor is insensitive to the time of data acquisition, effect of laboratory site, type of gene chip, and phenotypic status. Based on accurate allele frequency estimates, analytic methods based on individual-level allele frequencies are developed and successfully applied to discover genomic patterns of allele frequencies, detect chromosomal abnormalities, classify sample groups, identify outlier samples, and estimate the purity of tumor samples. The methods are packaged into a new analysis tool, ALOHA (Allele-frequency/Loss-of-heterozygosity/Allele-imbalance). CONCLUSIONS: This is the first time that these important genetic/genomic applications have been simultaneously conducted by the analyses of individual-level allele frequencies estimated by a unified intensity-measuring approach. We expect that additional practical applications for allele frequency analysis will be found. The developed databases and tools provide useful resources for human genome analysis via high-throughput single-nucleotide-polymorphism arrays. The ALOHA software was written in R and R GUI and can be downloaded at http://www.stat.sinica.edu.tw/hsinchou/genetics/aloha/ALOHA.htm.

Dataset Information

Allele frequency changes due to hitch-hiking in genomic selection programs.

Background

Methods

Results

Conclusions

Publications

Allele frequency changes due to hitch-hiking in genomic selection programs.

Similar Datasets

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